Rhyme Finder

Found poetry

More "found poetry"

http://mrsvanhekken.blogspot.com/2013/08/found-poetry.html

Tristan Tzara

in 1920

http://rethinked.org/?tag=dada

It is experimental in the sense of being something to do.

 – William S. Burroughs

http://www.remixthebook.com/the-course/cut-ups

Tech details

• Used RiTa.js to get "similar sounding words" based on line endings
• Search for line endings that match the input by similar sound (more tractable than searching for ANY word anywhere)
• Concatenate lines found

Some randomness

also built in...

Let's make it more visual...

Less useful in poetry... but cool for other reasons.

It's a terrible day, but your fingers are safe!

• What's a "line ending?" The RiTa sentence tokenizer was not good.
• I dumbly used "\n" to get more matches.
• It's slow to build the initial matches hash
• Meter and rhyme would be better (Allison's pronouncing lib)
• Are character names a plus or minus?

Fantastical Britain,

A Map for Allison

https://twitter.com/aparrish/status/717380189081235456

(Remind people what the UK looks like...)

Map

Can we do even better than the real British town names? 

• Neural nets that don't need to worry about grammar/syntax are fast to train and use.
• So I adapted Karpathy's RNN js code to use just the trained model in pure js.  That's cool.
• Bought UK town names data, trained on it.
• Plugged in model.json file & a sqlite file for Lat/Lons -- no server needed!  (Even cooler.)

tl;dr:  No, but it was fun.

http://cs.stanford.edu/people/karpathy/recurrentjs/

Training data...

demo

Not really better than the real thing...

"Todlewitch" & "Cople-thave"

SQL.js is really cool... load a .sqlite file (my CSV of town names converted to SQLite) and query it in JS. No server!

Finding towns between the map view bounds:

I replace their names on the map with on-demand neural net model-generated output (but keep the real names for the popups)

Genetic Castles

Genetic Algorithms

• Evolutionary development: Gene pool, random variation, a fitness function.
  • Attributes are encoded in ranges of values (in this code each is 0-1, mapped to the "real" ranges)
  • Result of the "genes" is evaluated according to the fitness function, and new generations evolve combining the "best" survivors-- plus some randomness.

See, e.g., Shiffman, http://natureofcode.com/book/chapter-9-the-evolution-of-code/

"A Genetic Algorithm of Flowers"

Clay Heaton, processing repo

Jared Tarbell's Combinatoric Critters

Adding user interaction -- voting -- is awesome. Now I decide fitness!

Shiffman's demo:

Your idea of fitness can change... based on what you see or how you feel.

source

But:  

I am shit at drawing with Processing.

demo

So I bought art.

Artist: Saiana

demo

MadameBricolage on Etsy

Similar things I bought on Etsy

Ivanhoe

Cleaning up text to make it artistic

• Real emdashes
• Curly quotes
• Paragraph indents
• Real fonts
• Format names "better"

http://localhost:8001/castle_gen/

To Do

• Save output of your favs
• Vector art would be better, but p5.svg didn't work well for me
• Save "DNA/script" for the ones that you like
• Try a GA with text as output

Cocktail Recipes

source

Jordan Meyer did a great talk with NYT scraped cocktail recipes.

https://github.com/jordanmeyer/nyt-bar-optimizer

His ingredients data... suggests remixing.

"Sasquatch 110oz Extremely Large Cocktail Shaker"

A lot of iterated, tuned rules

A lot of tiny vocab data sets (sigh)

SentiNet, WordNet (extracted from the dict), made up...

Some design principles

• sugar, honey : "positive" words (per SentiWordNet)
• bitters : "negative" words
• lots more herbs and fruits come into play
• ice and water come in more forms (hail, snow, lakewater...)
• alcohols are substituted with other drink types and maybe drugs like prozac
• Club sodas come in varieties, like "book club soda", "golf club soda"
• when all other rules fail, use a word that sounds similar (RiTa.js) -- some of the best results!

new mythologies: the lakewatermelon

"a dash of nutmeg" :

"a dash of nightmare"

"an ounce of cream" :

"an ounce of scream"

"Serendipitous" bugs

Demo

This was a very manual authoring process.

• But it made me laugh more than the others!
• Generate recipes, tune rules... ad infinitum
• Lists of words were not automatically findable.
• Obviously a "simpler" approach might be plausible, like using word2vec or an RNN, but we also want it to be "funny" and "different"
• How can this be made easier?